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Multichannel time encoding with integrate-and-fire neurons

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Aurel A. LazarAuthors Info & Claims

Neurocomputing, Volume 65-66

Pages 401 - 407

https://doi.org/10.1016/j.neucom.2004.10.034

Published: 01 June 2005 Publication History

Abstract

Time encoding is a mechanism of mapping amplitude information into a time sequence. We show that multichannel time encoding using filter banks and integrate-and-fire neurons provides, under natural conditions, an invertible representation of information, i.e., a sensory stimulus can be recovered from its multidimensional spike train representation loss-free. We describe an algorithm for perfect stimulus recovery and derive conditions that guarantee its convergence.

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A.A. Lazar, Time encoding with filter banks and integrate-and-fire neurons, BNET Technical Report, BNET #2-03, Department of Electrical Engineering, Columbia University, New York, NY 10027, September 2003.

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Witherspoon BYoung A(2024)Event-Driven Sensing and Embedded Neuromorphic Platforms for Gamma Radiation MonitoringProceedings of the Great Lakes Symposium on VLSI 202410.1145/3649476.3660363(779-784)Online publication date: 12-Jun-2024
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Thao NRzepka DMiśkowicz M(2023)Bandlimited Signal Reconstruction From Leaky Integrate-and-Fire Encoding Using POCSIEEE Transactions on Signal Processing10.1109/TSP.2023.325626971(1464-1479)Online publication date: 1-Jan-2023
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Adam KScholefield AVetterli M(2022)Asynchrony Increases Efficiency: Time Encoding of Videos and Low-Rank SignalsIEEE Transactions on Signal Processing10.1109/TSP.2021.313370970(105-116)Online publication date: 1-Jan-2022
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Neurocomputing Volume 65-66, Issue

June, 2005

901 pages

ISSN:0925-2312

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 June 2005

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Witherspoon BYoung A(2024)Event-Driven Sensing and Embedded Neuromorphic Platforms for Gamma Radiation MonitoringProceedings of the Great Lakes Symposium on VLSI 202410.1145/3649476.3660363(779-784)Online publication date: 12-Jun-2024
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Thao NRzepka DMiśkowicz M(2023)Bandlimited Signal Reconstruction From Leaky Integrate-and-Fire Encoding Using POCSIEEE Transactions on Signal Processing10.1109/TSP.2023.325626971(1464-1479)Online publication date: 1-Jan-2023
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Florescu DCoca D(2018)Identification of linear and nonlinear sensory processing circuits from spiking neuron dataNeural Computation10.1162/neco_a_0105130:3(670-707)Online publication date: 1-Mar-2018
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Lazar A(2010)Population encoding with Hodgkin-Huxley neuronsIEEE Transactions on Information Theory10.1109/TIT.2009.203704056:2(821-837)Online publication date: 1-Feb-2010
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Lazar APnevmatikakis E(2009)Reconstruction of sensory stimuli encoded with integrate-and-fire neurons with random thresholdsEURASIP Journal on Advances in Signal Processing10.1155/2009/6829302009(1-14)Online publication date: 1-Jan-2009
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Lazar APnevmatikakis E(2008)Faithful representation of stimuli with a population of integrate-and-fire neuronsNeural Computation10.1162/neco.2008.06-07-55920:11(2715-2744)Online publication date: 1-Nov-2008
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